Step Length, but Not Stepping Cadence, Strongly Predicts Physical Activity Intensity during Jogging and Running

Device-based measures often rely on the positive relationship between walking cadence and metabolic equivalents of task (METs) to estimate physical activity. It is unknown whether this relationship remains during jogging/running. The study purpose was to investigate the relationships between METs, cadence, and step length during walking and jogging/running. A treadmill protocol with 5 walking (3.2-6.4 km•hr[superscript -1]) and 5 jogging/running stages (8.0-11.3 km•hr[superscript -1]) was completed in 43 adults (23 ± 5 years, 19[female gender symbol]). Predictors of METs during walking and jogging/running were determined by generalized mixed modeling. The strongest prediction models for walking (R[superscript 2] = 0.72, P < 0.001) and jogging/running (R[superscript 2] = 0.75, P < 0.001) included cadence[superscript 2], cadence, step length, age, and leg length (all, P < 0.001). Step length accounted for 49.1% and 78.3% of model variance during walking and jogging/running, respectively. METs are poorly estimated by cadence during jogging/running but step length reduces error. Strategies to measure step length in free-living settings could better predict physical activity intensity.